2D Visual Object Tracking Lecture
Nowadays, digital videos are everywhere and revolutionize very many domains, notably:
-Digital Media (video/movie) Content Production and Broadcasting,
-Social Media Streaming and Analytics (g., YouTube),
-Mobile computing and streaming
-Videoconferencing
-Medical/Biological/Dental Imaging and Diagnosis,
-Big Visual Data Analytics,
-Internet and Communications (media broadcasting, streaming).
-Scientific Imaging of any sort, e.g., Physics.
Furthermore, Video Processing and Analysis enables diverse applications, in unison with Computer Vision and Machine Learning:
-Autonomous Systems (cars, drones, vessels) Perception,
-Robotics Perception and Control,
-Intelligent Human-Machine Interaction,
-Anthropocentric (human-centered) Computing,
-Smart Cities/Buildings and Assisted living.
Visual Computing, encompassing Computer Vision and Video Processing and Analysis, coupled with AI (notably Machine Learning and Deep Neural Network) advances hit the news almost every day.
Object/Target tracking is a crucial component of many vision systems. Object tracking issues are overviewed, e.g., occlusion handling, feature loss, drifting to the backgound. Many approaches regarding person/object detection and tracking in videos have been proposed. In this lecture, video tracking methods using correlation filters or convolutional neural networks are presented, focusing on video trackers that are capable of achieving real-time performance for long-term tracking on embedded computing platforms. Joint object detection and tracking methods are detailed. Tracking performance metrics are overviewed.